Machine Learning is the subarea of Artificial Intelligence (A.I). It explores the construction of algorithms that can learn from data. Through Machine Learning the algorithms (in general, not just in advertising) are able to teach themselves to perform certain tasks, like recognition, planning, prediction, etc...

Machine Learning algorithms in programmatic advertising help us define our best audience and navigate our buying strategies in the most relevant way to meet their preferences. The audience understanding is indeed a vast process, now significantly improved by the power of programmatic technologies. The number of online users is rapidly growing - additional 225 million new users only for the last 12 months. To put this in a bit more concrete perspective: every action of each and every one of these users leaves a trace. These traces are like the footprints of steps, and when examined closely they can show us particular information about the person who left them.

In the world of Big Data and audience measurement, each trace represents a data point (now you can envision why Big Data is called “big” and not “moderately large data”). Thanks to programmatic technologies, each data point can be collected and used in different ways to help us create a more complete profile of our consumers- it can include information related to the geographical location of the user, his interests, age, gender.

This is where Machine Learning algorithms come in place. They not only help us collect all of the footprints of our users but they allow us to derive meaningful information out of them. Thanks to the comprehensive data analyses that they are able to conduct, we can get a better perspective on what groups of people will be best to target and where to find them, what are their buying habits, what are their interests, their preferred channels of interaction, etc.

Knowledge is power. And in the world of digital advertising, better informed knowledge on the prospect audience is the path to achieving more profitable results.